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1. Neuro-telehealth for fragile patients in a tertiary referral neurological institute during the COVID-19 pandemic in Milan, Lombardy

Author

Pareyson, D, Pantaleoni, C, Eleopra, R, De Filippis, G, Moroni, I, Freri, E, Zibordi, F, Bulgheroni, S, Pagliano, E, Sarti, D, Silvani, A, Grazzi, L, Tiraboschi, P, Didato, G, Anghileri, E, Bersano, A, Valentini, L, Piacentini, S, Muscio, C, Leonardi, M, Mariotti, C, Eoli, M, Nuzzo, S, Tagliavini, F, Confalonieri, P, De Giorgi, F, Antozzi, C, Ardissone, A, Bersano, E, Boncoraglio, G, Bonvegna, S, Botturi, A, Brambilla, L, Canafoglia, L, Caputi, L, Caroppo, P, Carriero, M, Casali, C, Casazza, M, Catania, A, Ciaccio, C, Cilia, R, Dallabella, E, D'Amico, D, Danti, F, D'Arrigo, S, Decurtis, M, Deleo, F, Devigili, G, Difede, G, Digiacomo, R, Elia, A, Esposito, S, Estienne, M, Fenu, S, Fichera, M, Finocchiaro, G, Frangiamore, R, Gatti, M, Gaviani, P, Giaccone, G, Giani, L, Giovagnoli, A, Andreasi, N, Granata, T, Granocchio, E, Lamperti, C, Lamperti, E, Leone, M, Masson, R, Nanetti, L, Nardocci, N, Pastori, C, Pisciotta, C, Cecchini, A, Ragona, F, Redaelli, V, Saletti, V, Salsano, E, Scelzo, E, Solazzi, R, Tozzo, A, Usai, S, Zorzi, G, Arnoldi, M, Foscan, M, Marchi, A, Pedrinelli, I, Zanin, R, Gazzola, S, Magazu, S, Scopelliti, M, Casalino, T, Desalvatore, M, Mazzanti, S, Taddei, M, Fedeli, A, Sattin, D, Galimberti, L, Zagari, R, Bombonato, M, Fonte, L, Floridia, S, Pareyson D., Pantaleoni C., Eleopra R., De Filippis G., Moroni I., Freri E., Zibordi F., Bulgheroni S., Pagliano E., Sarti D., Silvani A., Grazzi L., Tiraboschi P., Didato G., Anghileri E., Bersano A., Valentini L., Piacentini S., Muscio C., Leonardi M., Mariotti C., Eoli M., Nuzzo S., Tagliavini F., Confalonieri P., De Giorgi F., Antozzi C., Ardissone A., Bersano E., Boncoraglio G., Bonvegna S., Botturi A., Brambilla L., Canafoglia L., Caputi L., Caroppo P., Carriero M. R., Casali C., Casazza M., Catania A., Ciaccio C., Cilia R., DallaBella E., D'Amico D., Danti F. R., D'Arrigo S., DeCurtis M., Deleo F., Devigili G., DiFede G., DiGiacomo R., Elia A., Esposito S., Estienne M., Fenu S., Fichera M., Finocchiaro G., Frangiamore R., Gatti M., Gaviani P., Giaccone G., Giani L., Giovagnoli A. R., Andreasi N. G., Granata T., Granocchio E., Lamperti C., Lamperti E., Leone M., Masson R., Nanetti L., Nardocci N., Pastori C., Pisciotta C., Cecchini A. P., Ragona F., Redaelli V., Saletti V., Salsano E., Scelzo E., Solazzi R., Tozzo A., Usai S., Zorzi G., Arnoldi M. T., Foscan M., Marchi A., Pedrinelli I., Zanin R., Gazzola S., Magazu S., Scopelliti M. R., Casalino T., DeSalvatore M., Mazzanti S., Taddei M., Fedeli A., Sattin D., Galimberti L., Zagari R., Bombonato M., Fonte L., Floridia S., Pareyson, D, Pantaleoni, C, Eleopra, R, De Filippis, G, Moroni, I, Freri, E, Zibordi, F, Bulgheroni, S, Pagliano, E, Sarti, D, Silvani, A, Grazzi, L, Tiraboschi, P, Didato, G, Anghileri, E, Bersano, A, Valentini, L, Piacentini, S, Muscio, C, Leonardi, M, Mariotti, C, Eoli, M, Nuzzo, S, Tagliavini, F, Confalonieri, P, De Giorgi, F, Antozzi, C, Ardissone, A, Bersano, E, Boncoraglio, G, Bonvegna, S, Botturi, A, Brambilla, L, Canafoglia, L, Caputi, L, Caroppo, P, Carriero, M, Casali, C, Casazza, M, Catania, A, Ciaccio, C, Cilia, R, Dallabella, E, D'Amico, D, Danti, F, D'Arrigo, S, Decurtis, M, Deleo, F, Devigili, G, Difede, G, Digiacomo, R, Elia, A, Esposito, S, Estienne, M, Fenu, S, Fichera, M, Finocchiaro, G, Frangiamore, R, Gatti, M, Gaviani, P, Giaccone, G, Giani, L, Giovagnoli, A, Andreasi, N, Granata, T, Granocchio, E, Lamperti, C, Lamperti, E, Leone, M, Masson, R, Nanetti, L, Nardocci, N, Pastori, C, Pisciotta, C, Cecchini, A, Ragona, F, Redaelli, V, Saletti, V, Salsano, E, Scelzo, E, Solazzi, R, Tozzo, A, Usai, S, Zorzi, G, Arnoldi, M, Foscan, M, Marchi, A, Pedrinelli, I, Zanin, R, Gazzola, S, Magazu, S, Scopelliti, M, Casalino, T, Desalvatore, M, Mazzanti, S, Taddei, M, Fedeli, A, Sattin, D, Galimberti, L, Zagari, R, Bombonato, M, Fonte, L, Floridia, S, Pareyson D., Pantaleoni C., Eleopra R., De Filippis G., Moroni I., Freri E., Zibordi F., Bulgheroni S., Pagliano E., Sarti D., Silvani A., Grazzi L., Tiraboschi P., Didato G., Anghileri E., Bersano A., Valentini L., Piacentini S., Muscio C., Leonardi M., Mariotti C., Eoli M., Nuzzo S., Tagliavini F., Confalonieri P., De Giorgi F., Antozzi C., Ardissone A., Bersano E., Boncoraglio G., Bonvegna S., Botturi A., Brambilla L., Canafoglia L., Caputi L., Caroppo P., Carriero M. R., Casali C., Casazza M., Catania A., Ciaccio C., Cilia R., DallaBella E., D'Amico D., Danti F. R., D'Arrigo S., DeCurtis M., Deleo F., Devigili G., DiFede G., DiGiacomo R., Elia A., Esposito S., Estienne M., Fenu S., Fichera M., Finocchiaro G., Frangiamore R., Gatti M., Gaviani P., Giaccone G., Giani L., Giovagnoli A. R., Andreasi N. G., Granata T., Granocchio E., Lamperti C., Lamperti E., Leone M., Masson R., Nanetti L., Nardocci N., Pastori C., Pisciotta C., Cecchini A. P., Ragona F., Redaelli V., Saletti V., Salsano E., Scelzo E., Solazzi R., Tozzo A., Usai S., Zorzi G., Arnoldi M. T., Foscan M., Marchi A., Pedrinelli I., Zanin R., Gazzola S., Magazu S., Scopelliti M. R., Casalino T., DeSalvatore M., Mazzanti S., Taddei M., Fedeli A., Sattin D., Galimberti L., Zagari R., Bombonato M., Fonte L., and Floridia S.

Abstract

Background: Lombardy was severely hit by the COVID-19 pandemic since February 2020 and the Health System underwent rapid reorganization. Outpatient clinics were stopped for non-urgent patients: it became a priority to manage hundreds of fragile neurological patients who suddenly had less reference points. In Italy, before the pandemic, Televisits were neither recognized nor priced. Methods: At the Fondazione IRCCS Istituto Neurologico C. Besta, we reorganized outpatient clinics to deliver Neuro-telemedicine services, including Televisits and Teleneurorehabilitation, since March 2020. A dedicated Working Group prepared the procedure, tested the system, and designed satisfaction questionnaires for adults and children. Results: After a pilot phase, we prepared a procedure for Telemedicine outpatient clinics which was approved by hospital directions. It included prescription, booking, consenting, privacy and data protection, secure connection with patients (Teams Microsoft 365), electronic report preparation and delivery, reporting, and accountability of the services. During the March–September 2020 period, we delivered 3167 Telemedicine services, including 1618 Televisits, to 1694 patients (972 adults, 722 children) with a wide range of chronic neurological disorders. We successfully administered different clinical assessment and scales. Satisfaction among patients and caregivers was very high. Conclusions: During the dramatic emergency, we were able to take care of more than 1600 patients by organizing Neuro-telehealth in a few weeks, lessening the impact of the pandemic on fragile patients with chronic neurological disorders; this strategy is now stably embedded in our care pathways. In Italy, Telehealth is at present recognized and priced and is becoming a stable pillar of the health system.

Published
2021

2. Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment

Author

Tondo, G, Boccalini, C, Vanoli, E, Presotto, L, Muscio, C, Ciullo, V, Banaj, N, Piras, F, Filippini, G, Tiraboschi, P, Tagliavini, F, Frisoni, G, Cappa, S, Spalletta, G, Perani, D, Tondo, Giacomo, Boccalini, Cecilia, Vanoli, Emilia Giovanna, Presotto, Luca, Muscio, Cristina, Ciullo, Valentina, Banaj, Nerisa, Piras, Federica, Filippini, Graziella, Tiraboschi, Pietro, Tagliavini, Fabrizio, Frisoni, Giovanni Battista, Cappa, Stefano F, Spalletta, Gianfranco, Perani, Daniela, Tondo, G, Boccalini, C, Vanoli, E, Presotto, L, Muscio, C, Ciullo, V, Banaj, N, Piras, F, Filippini, G, Tiraboschi, P, Tagliavini, F, Frisoni, G, Cappa, S, Spalletta, G, Perani, D, Tondo, Giacomo, Boccalini, Cecilia, Vanoli, Emilia Giovanna, Presotto, Luca, Muscio, Cristina, Ciullo, Valentina, Banaj, Nerisa, Piras, Federica, Filippini, Graziella, Tiraboschi, Pietro, Tagliavini, Fabrizio, Frisoni, Giovanni Battista, Cappa, Stefano F, Spalletta, Gianfranco, and Perani, Daniela

Abstract

Background and ObjectiveThis was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-mild cognitive impairment [pre-MCI]).MethodsData were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism.ResultsA total of 105 participants (SCD = 49, pre-MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions.DiscussionFDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI. These results indicate that SCD and pre-MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neu

Published
2022

3. Accuracy of the clinical diagnosis of dementia with Lewy bodies (DLB) among the Italian Dementia Centers: a study by the Italian DLB study group (DLB-SINdem)

Author

Russo, M., Carrarini, Claudia, Di Iorio, A., Pellegrino, R., Bruni, A. C., Caratozzolo, S., Chiari, A., Pretta, S., Marra, Camillo, Cotelli, M. S., Arighi, A., Fumagalli, G. G., Cataruzza, T., Caso, F., Paci, C., Rosso, M., Amici, S., Giannandrea, D., Pilotto, A., Luzzi, S., Castellano, A., D'Antonio, F., Luca, A., Gelosa, G., Piccoli, T., Mauri, M., Agosta, F., Babiloni, C., Borroni, B., Bozzali, M., Filippi, M., Galimberti, D., Monastero, R., Muscio, C., Parnetti, L., Perani, D., Serra, L., Silani, V., Tiraboschi, P., Cagnin, A., Padovani, A., Bonanni, L., Roberta, B., Federica, F., Sebastiano, G., Caterina, G., Gianmarco, G., Giuseppe, M., Giulia, M., Stefano, M., Carmela, R., Marco, R., Pierpaolo, S., Giuseppe, S. P., Marinella, T., Federico, V., Antonietta, V. M., Carrarini C., Marra C. (ORCID:0000-0003-3994-4044), Russo, M., Carrarini, Claudia, Di Iorio, A., Pellegrino, R., Bruni, A. C., Caratozzolo, S., Chiari, A., Pretta, S., Marra, Camillo, Cotelli, M. S., Arighi, A., Fumagalli, G. G., Cataruzza, T., Caso, F., Paci, C., Rosso, M., Amici, S., Giannandrea, D., Pilotto, A., Luzzi, S., Castellano, A., D'Antonio, F., Luca, A., Gelosa, G., Piccoli, T., Mauri, M., Agosta, F., Babiloni, C., Borroni, B., Bozzali, M., Filippi, M., Galimberti, D., Monastero, R., Muscio, C., Parnetti, L., Perani, D., Serra, L., Silani, V., Tiraboschi, P., Cagnin, A., Padovani, A., Bonanni, L., Roberta, B., Federica, F., Sebastiano, G., Caterina, G., Gianmarco, G., Giuseppe, M., Giulia, M., Stefano, M., Carmela, R., Marco, R., Pierpaolo, S., Giuseppe, S. P., Marinella, T., Federico, V., Antonietta, V. M., Carrarini C., and Marra C. (ORCID:0000-0003-3994-4044)

Abstract

Introduction: Dementia with Lewy bodies (DLB) may represent a diagnostic challenge, since its clinical picture overlaps with other dementia. Two toolkits have been developed to aid the clinician to diagnose DLB: the Lewy Body Composite Risk Score (LBCRS) and the Assessment Toolkit for DLB (AT-DLB). We aim to evaluate the reliability of these two questionnaires, and their ability to enhance the interpretation of the international consensus diagnostic criteria. Methods: LBCRS and AT-DLB were distributed to 135 Italian Neurological Centers for Cognitive Decline and Dementia (CDCDs), with the indication to administer them to all patients with dementia referred within the subsequent 3 months. We asked to subsequently apply consensus criteria for DLB diagnosis, to validate the diagnostic accuracy of the two toolkits. Results: A total of 23 Centers joined the study; 1854 patients were enrolled. We found a prevalence of possible or probable DLB of 13% each (26% total), according to the consensus criteria. LBCRS toolkit showed good reliability, with a Cronbach alpha of 0.77, stable even after removing variables from the construct. AT-DLB toolkit Cronbach alpha was 0.52 and, after the subtraction of the “cognitive fluctuation” criterion, was only 0.31. Accuracy, sensitivity, and specificity were higher for LBCRS vs. AT-DLB. However, when simultaneously considered in the logistic models, AT-DLB showed a better performance (p < 0.001). Overall, the concordance between LBCRS positive and AT-DLB possible/probable was of 78.02% Conclusions: In a clinical setting, the LBCRS and AT-DLB questionnaires have good accuracy for DLB diagnosis.

Published
2022

4. Neuro-telehealth for fragile patients in a tertiary referral neurological institute during the COVID-19 pandemic in Milan, Lombardy

Author

Pareyson D., Pantaleoni C., Eleopra R., De Filippis G., Moroni I., Freri E., Zibordi F., Bulgheroni S., Pagliano E., Sarti D., Silvani A., Grazzi L., Tiraboschi P., Didato G., Anghileri E., Bersano A., Valentini L., Piacentini S., Muscio C., Leonardi M., Mariotti C., Eoli M., Nuzzo S., Tagliavini F., Confalonieri P., De Giorgi F., Antozzi C., Ardissone A., Bersano E., Boncoraglio G., Bonvegna S., Botturi A., Brambilla L., Canafoglia L., Caputi L., Caroppo P., Carriero M. R., Casali C., Casazza M., Catania A., Ciaccio C., Cilia R., DallaBella E., D'Amico D., Danti F. R., D'Arrigo S., DeCurtis M., Deleo F., Devigili G., DiFede G., DiGiacomo R., Elia A., Esposito S., Estienne M., Fenu S., Fichera M., Finocchiaro G., Frangiamore R., Gatti M., Gaviani P., Giaccone G., Giani L., Giovagnoli A. R., Andreasi N. G., Granata T., Granocchio E., Lamperti C., Lamperti E., Leone M., Masson R., Nanetti L., Nardocci N., Pastori C., Pisciotta C., Cecchini A. P., Ragona F., Redaelli V., Saletti V., Salsano E., Scelzo E., Solazzi R., Tozzo A., Usai S., Zorzi G., Arnoldi M. T., Foscan M., Marchi A., Pedrinelli I., Zanin R., Gazzola S., Magazu S., Scopelliti M. R., Casalino T., DeSalvatore M., Mazzanti S., Taddei M., Fedeli A., Sattin D., Galimberti L., Zagari R., Bombonato M., Fonte L., Floridia S., Pareyson, D, Pantaleoni, C, Eleopra, R, De Filippis, G, Moroni, I, Freri, E, Zibordi, F, Bulgheroni, S, Pagliano, E, Sarti, D, Silvani, A, Grazzi, L, Tiraboschi, P, Didato, G, Anghileri, E, Bersano, A, Valentini, L, Piacentini, S, Muscio, C, Leonardi, M, Mariotti, C, Eoli, M, Nuzzo, S, Tagliavini, F, Confalonieri, P, De Giorgi, F, Antozzi, C, Ardissone, A, Bersano, E, Boncoraglio, G, Bonvegna, S, Botturi, A, Brambilla, L, Canafoglia, L, Caputi, L, Caroppo, P, Carriero, M, Casali, C, Casazza, M, Catania, A, Ciaccio, C, Cilia, R, Dallabella, E, D'Amico, D, Danti, F, D'Arrigo, S, Decurtis, M, Deleo, F, Devigili, G, Difede, G, Digiacomo, R, Elia, A, Esposito, S, Estienne, M, Fenu, S, Fichera, M, Finocchiaro, G, Frangiamore, R, Gatti, M, Gaviani, P, Giaccone, G, Giani, L, Giovagnoli, A, Andreasi, N, Granata, T, Granocchio, E, Lamperti, C, Lamperti, E, Leone, M, Masson, R, Nanetti, L, Nardocci, N, Pastori, C, Pisciotta, C, Cecchini, A, Ragona, F, Redaelli, V, Saletti, V, Salsano, E, Scelzo, E, Solazzi, R, Tozzo, A, Usai, S, Zorzi, G, Arnoldi, M, Foscan, M, Marchi, A, Pedrinelli, I, Zanin, R, Gazzola, S, Magazu, S, Scopelliti, M, Casalino, T, Desalvatore, M, Mazzanti, S, Taddei, M, Fedeli, A, Sattin, D, Galimberti, L, Zagari, R, Bombonato, M, Fonte, L, and Floridia, S

Subjects
Adult, medicine.medical_specialty, Telemedicine, Neurology, Referral, Dermatology, Telehealth, 03 medical and health sciences, 0302 clinical medicine, Pandemic, medicine, Humans, Outpatient clinic, 030212 general & internal medicine, Medical prescription, Child, Pandemics, Referral and Consultation, SARS-CoV-2, business.industry, Teleneurorehabilitation, COVID-19, General Medicine, medicine.disease, Televisit, Psychiatry and Mental health, Italy, Neuro-telehealth, Neurology (clinical), Neurosurgery, Medical emergency, business, 030217 neurology & neurosurgery
Abstract

Background: Lombardy was severely hit by the COVID-19 pandemic since February 2020 and the Health System underwent rapid reorganization. Outpatient clinics were stopped for non-urgent patients: it became a priority to manage hundreds of fragile neurological patients who suddenly had less reference points. In Italy, before the pandemic, Televisits were neither recognized nor priced. Methods: At the Fondazione IRCCS Istituto Neurologico C. Besta, we reorganized outpatient clinics to deliver Neuro-telemedicine services, including Televisits and Teleneurorehabilitation, since March 2020. A dedicated Working Group prepared the procedure, tested the system, and designed satisfaction questionnaires for adults and children. Results: After a pilot phase, we prepared a procedure for Telemedicine outpatient clinics which was approved by hospital directions. It included prescription, booking, consenting, privacy and data protection, secure connection with patients (Teams Microsoft 365), electronic report preparation and delivery, reporting, and accountability of the services. During the March–September 2020 period, we delivered 3167 Telemedicine services, including 1618 Televisits, to 1694 patients (972 adults, 722 children) with a wide range of chronic neurological disorders. We successfully administered different clinical assessment and scales. Satisfaction among patients and caregivers was very high. Conclusions: During the dramatic emergency, we were able to take care of more than 1600 patients by organizing Neuro-telehealth in a few weeks, lessening the impact of the pandemic on fragile patients with chronic neurological disorders; this strategy is now stably embedded in our care pathways. In Italy, Telehealth is at present recognized and priced and is becoming a stable pillar of the health system.

Published
2021
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5. Robust MR-free Grey Matter Extraction in Amyloid PET/CT Studies with Deep Learning

Author

Presotto, L, Bezzi, C, Vanoli, G, Muscio, C, Tagliavini, F, Perani, D, Bettinardi, V, Presotto L., Bezzi C., Vanoli G., Muscio C., Tagliavini F., Perani D., Bettinardi V., Presotto, L, Bezzi, C, Vanoli, G, Muscio, C, Tagliavini, F, Perani, D, Bettinardi, V, Presotto L., Bezzi C., Vanoli G., Muscio C., Tagliavini F., Perani D., and Bettinardi V.

Abstract

Quantification of amyloid PET studies is most accurate if regions of interest (ROIs) are not affected by the presence of cerebrospinal fluid. Patients with high amyloid load often have great atrophy, therefore, the use of atlas-based ROIs, instead of patient specific anatomy, can underestimate amyloid load, leading to a bias. Traditionally, this can be overcome only using MR anatomical sequences, which are burdensome and might not be ideal to be performed for each patient in the clinical routine. In this work, we propose to overcome this issue by using a method based on deep learning. As CT scans provide anatomical information, even at the very low doses used for PET attenuation correction, we propose the use of such a scan, together with the PET one, for a U-NET based segmentation. The approach achieves a median DICE score of 77% on a validation cohort of N=20 patients, even when using only N=14 patients in the training dataset. A dedicated data augmentation strategy is used, and the individual contribution of each modality is analyzed. We find that the joint effect of PET and CT is beneficial (median DICE: PET only 73.0%, CT only 74%). A near perfect correlation with MR-based quantification was also found.

Published
2020

6. Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification

Author

Presotto, L, Iaccarino, L, Sala, A, Vanoli, E, Muscio, C, Nigri, A, Bruzzone, M, Tagliavini, F, Gianolli, L, Perani, D, Bettinardi, V, Presotto L., Iaccarino L., Sala A., Vanoli E. G., Muscio C., Nigri A., Bruzzone M. G., Tagliavini F., Gianolli L., Perani D., Bettinardi V., Presotto, L, Iaccarino, L, Sala, A, Vanoli, E, Muscio, C, Nigri, A, Bruzzone, M, Tagliavini, F, Gianolli, L, Perani, D, Bettinardi, V, Presotto L., Iaccarino L., Sala A., Vanoli E. G., Muscio C., Nigri A., Bruzzone M. G., Tagliavini F., Gianolli L., Perani D., and Bettinardi V.

Abstract

The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT (18F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global 18F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVrCT SUVrMRI) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVrCT and SUVrMRI global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine a

Published
2018

7. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort

Author

Russell, L.L. (Lucy L.), Greaves, C.V. (Caroline V.), Bocchetta, M. (Martina), Nicholas, J.M. (Jennifer), Convery, R.S. (Rhian S.), Moore, K. (Katrina), Cash, D.M. (David M.), Swieten, J.C. (John) van, Jiskoot, L.C. (Lize), Moreno, F. (Fermin), Sánchez-Valle, R. (Raquel), Borroni, B. (Barbara), Laforce, R. (Robert), Masellis, M. (Mario), Tartaglia, M.C. (Maria Carmela), Graff, C. (Caroline), Rotondo, E. (Emanuela), Galimberti, D. (Daniela), Rowe, J.B. (James), Finger, E. (Elizabeth), Synofzik, M. (Matthis), Vandenberghe, R. (Rik), De Mendonça, A. (Alexandre), Tagliavini, F. (Fabrizio), Santana, I. (Isabel), Ducharme, S. (Simon), Butler, C. (Chris), Gerhard, A. (Alex), Levin, J. (Johannes), Danek, A. (Adrian), Otto, M. (Markus), Warren, J.D. (Jason), Rohrer, J.D. (Jonathan), Rossor, M. (Martin), Fox, N.C. (Nick), Woollacott, I.O.C. (Ione O.C.), Shafei, R. (Rachelle), Heller, C. (Carolin), Guerreiro, R. (Rita), Bras, J. (Jose), Thomas, D.L. (David L), Mead, S. (Simon), Meeter, L.H.H. (Lieke), Panman, J.L. (Jessica), Papma, J.M. (Janne), Poos, J.M. (Jackie), Thornton, A.S. (Andrew), Pijnenburg, Y. (Yolanda), Barandiaran, M. (Myriam), Indakoetxea, B. (Begoña), Gabilondo, A. (Alazne), Tainta, M. (Mikel), de Arriba, M. (Maria), Gorostidi, A. (Ana), Zulaica, M. (Miren), Villanua, J. (Jorge), Diaz, Z. (Zigor), Borrego-Ecija, S. (Sergi), Olives, J. (Jaume), Lladó, A. (Albert), Balasa, M. (Mircea), Antonell, A. (Anna), Bargallo, N. (Nuria), Premi, E. (Enrico), Cosseddu MPsych, M. (Maura), Gazzina, S. (Stefano), Padovani, A. (Alessandro), Gasparotti, R. (Roberto), Archetti, S. (Silvana), Black, S.E. (Sandra), Mitchell, S. (Sara), Rogaeva, E. (Ekaterina), Freedman, M. (Morris), Keren, R. (Ron), Tang-Wai, D. (Daid), Öijerstedt, L. (Linn), Andersson, C. (Christin), Jelic, S. (Svetislav Svetislav), Thonberg, H. (Håkan), Arighi, A. (Andrea), Fenoglio, C. (Chiara), Scarpini, E. (Elio), Fumagalli, G. (Giorgio), Cope, T. (Thomas), Timberlake, C. (Carolyn), Rittman, T. (Timothy), Shoesmith, C. (Christen), Bartha, R. (Robart), Rademakers, S. (Suzanne), Wilke, C. (Carlo), Karnarth, H.-O. (Hans-Otto), Bender, B. (Benjamin), Bruffaerts, R. (Rose), Vandamme, P. (Philip), Vandenbulcke, M. (Mathieu), Ferreira, C.B. (Catarina B.), Miltenberger, G. (Gabriel), Maruta MPsych, C. (Carolina), Verdelho, A. (Ana), Afonso, S. (Sónia), Taipa, R. (Ricardo), Caroppo, P. (Paola), Di Fede, G. (Giuseppe), Giaccone, G. (Giuseppe), Muscio, C. (Cristina), Prioni, S. (Sara), Redaelli, V. (Veronica), Rossi, G. (Giacomina), Tiraboschi, P. (Pietro), Duro NPsych, D. (Diana), Almeida, M.R. (Maria R.), Castelo-Branco, M. (Miguel), Leitão, M.J. (Maria J.), Tabuas-Pereira, M. (Miguel), Santiago, B. (Beatriz), Gauthier, S. (Serge), Rosa-Neto, P. (Pedro), Veldsman, M. (Michele), Thompson, P.M. (Paul), Langheinrich, T. (Tobias), Prix, C. (Catharina), Hoegen, T. (Tobias), Wlasich, E. (Elisabeth), Loosli, S. (Sandra), Schonecker, S. (Sonja), Semler, E. (Elisa), Anderl-Straub, S. (Sarah), Russell, L.L. (Lucy L.), Greaves, C.V. (Caroline V.), Bocchetta, M. (Martina), Nicholas, J.M. (Jennifer), Convery, R.S. (Rhian S.), Moore, K. (Katrina), Cash, D.M. (David M.), Swieten, J.C. (John) van, Jiskoot, L.C. (Lize), Moreno, F. (Fermin), Sánchez-Valle, R. (Raquel), Borroni, B. (Barbara), Laforce, R. (Robert), Masellis, M. (Mario), Tartaglia, M.C. (Maria Carmela), Graff, C. (Caroline), Rotondo, E. (Emanuela), Galimberti, D. (Daniela), Rowe, J.B. (James), Finger, E. (Elizabeth), Synofzik, M. (Matthis), Vandenberghe, R. (Rik), De Mendonça, A. (Alexandre), Tagliavini, F. (Fabrizio), Santana, I. (Isabel), Ducharme, S. (Simon), Butler, C. (Chris), Gerhard, A. (Alex), Levin, J. (Johannes), Danek, A. (Adrian), Otto, M. (Markus), Warren, J.D. (Jason), Rohrer, J.D. (Jonathan), Rossor, M. (Martin), Fox, N.C. (Nick), Woollacott, I.O.C. (Ione O.C.), Shafei, R. (Rachelle), Heller, C. (Carolin), Guerreiro, R. (Rita), Bras, J. (Jose), Thomas, D.L. (David L), Mead, S. (Simon), Meeter, L.H.H. (Lieke), Panman, J.L. (Jessica), Papma, J.M. (Janne), Poos, J.M. (Jackie), Thornton, A.S. (Andrew), Pijnenburg, Y. (Yolanda), Barandiaran, M. (Myriam), Indakoetxea, B. (Begoña), Gabilondo, A. (Alazne), Tainta, M. (Mikel), de Arriba, M. (Maria), Gorostidi, A. (Ana), Zulaica, M. (Miren), Villanua, J. (Jorge), Diaz, Z. (Zigor), Borrego-Ecija, S. (Sergi), Olives, J. (Jaume), Lladó, A. (Albert), Balasa, M. (Mircea), Antonell, A. (Anna), Bargallo, N. (Nuria), Premi, E. (Enrico), Cosseddu MPsych, M. (Maura), Gazzina, S. (Stefano), Padovani, A. (Alessandro), Gasparotti, R. (Roberto), Archetti, S. (Silvana), Black, S.E. (Sandra), Mitchell, S. (Sara), Rogaeva, E. (Ekaterina), Freedman, M. (Morris), Keren, R. (Ron), Tang-Wai, D. (Daid), Öijerstedt, L. (Linn), Andersson, C. (Christin), Jelic, S. (Svetislav Svetislav), Thonberg, H. (Håkan), Arighi, A. (Andrea), Fenoglio, C. (Chiara), Scarpini, E. (Elio), Fumagalli, G. (Giorgio), Cope, T. (Thomas), Timberlake, C. (Carolyn), Rittman, T. (Timothy), Shoesmith, C. (Christen), Bartha, R. (Robart), Rademakers, S. (Suzanne), Wilke, C. (Carlo), Karnarth, H.-O. (Hans-Otto), Bender, B. (Benjamin), Bruffaerts, R. (Rose), Vandamme, P. (Philip), Vandenbulcke, M. (Mathieu), Ferreira, C.B. (Catarina B.), Miltenberger, G. (Gabriel), Maruta MPsych, C. (Carolina), Verdelho, A. (Ana), Afonso, S. (Sónia), Taipa, R. (Ricardo), Caroppo, P. (Paola), Di Fede, G. (Giuseppe), Giaccone, G. (Giuseppe), Muscio, C. (Cristina), Prioni, S. (Sara), Redaelli, V. (Veronica), Rossi, G. (Giacomina), Tiraboschi, P. (Pietro), Duro NPsych, D. (Diana), Almeida, M.R. (Maria R.), Castelo-Branco, M. (Miguel), Leitão, M.J. (Maria J.), Tabuas-Pereira, M. (Miguel), Santiago, B. (Beatriz), Gauthier, S. (Serge), Rosa-Neto, P. (Pedro), Veldsman, M. (Michele), Thompson, P.M. (Paul), Langheinrich, T. (Tobias), Prix, C. (Catharina), Hoegen, T. (Tobias), Wlasich, E. (Elisabeth), Loosli, S. (Sandra), Schonecker, S. (Sonja), Semler, E. (Elisa), and Anderl-Straub, S. (Sarah)

Abstract

A key symptom of frontotemporal dementia (FTD) is difficulty interacting socially with others. Social cognition problems in FTD include impaired emotion processing and theory of mind difficulties, and whilst these have been studied extensively in sporadic FTD, few studies have investigated them in familial FTD. Facial Emotion Recognition (FER) and Faux Pas (FP) recognition tests were used to study social cognition within the Genetic Frontotemporal Dementia Initiative (GENFI), a large familial FTD cohort of C9orf72, GRN, and MAPT mutation carriers. 627 participants undertook at least one of the tasks, and were separated into mutation-negative healthy controls, presymptomatic mutation carriers (split into early and late groups) and symptomatic mutation carriers. Groups were compared using a linear regression model with bootstrapping, adjusting for age, sex, education, and for the FP recognition test, language. Neural correlates of social cognition deficits were explored using a voxel-based morphometry (VBM) study. All three of the symptomatic genetic groups were impaired on both tasks with no significant difference between them. However, prior to onset, only the late presymptomatic C9orf72 mutation carriers on the FER test were impaired compared to the control group, with a subanalysis showing differences particularly in fear and sadness. The VBM analysis revealed that impaired social cognition was mainly associated with a left hemisphere predominant network of regions involving particularly the striatum, orbitofrontal cortex and insula, and to a lesser extent the inferomedial temporal lobe and other areas of the frontal lobe. In conclusion, theory of mind and emotion processing abilities are impaired in familial FTD, with early changes occurring prior to symptom onset in C9orf72 presymptomatic mutation carriers. Future work should investigate how performance changes over time, in order to gain a clearer insight into social cognitive impairment over the course of the

Published
2020
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8. Social cognition impairment in genetic frontotemporal dementia within the GENFI cohort

Author

Russell, LL, Greaves, CV, Bocchetta, M, Nicholas, J, Convery, RS, Moore, K, Cash, DM, van Swieten, J.C., Jiskoot, Lize, Moreno, F, Sanchez-Valle, R, Borroni, B, Laforce, R, Jr, Masellis, M, Tartaglia, MC, Graff, C, Rotondo, E, Galimberti, D, Rowe, JB, Finger, E, Synofzik, M, Vandenberghe, R, Mendonça, A, Tagliavini, F, Santana, I, Ducharme, S, Butler, C, Gerhard, A, Levin, J, Danek, A, Otto, M, Warren, JD, Rohrer, JD, Rossor, MN, Fox, NC, Woollacott, IOC, Shafei, R, Heller, C, Guerreiro, R, Bras, J, Thomas, DL, Mead, S, Meeter, Lieke, Panman, J, Papma, J, Poos, J, van Minkelen, Rick, Al Pijnenburg, Y, Barandiaran, M, Indakoetxea, B, Gabilondo, A, Tainta, M, de Arriba, M, Gorostidi, A, Zulaica, M, Villanua, J, Diaz, Z, Borrego-Ecija, S, Olives, J, Lladó, A, Balasa, M, Antonell, A, Bargallo, N, Premi, E, Cosseddu Mpsych, M, Gazzina, S, Padovani, A, Gasparotti, R, Archetti, S, Black, S, Mitchell, S, Rogaeva, E, Freedman, M, Keren, R, Tang-Wai, D, Öijerstedt, L, Andersson, C, Jelic, V, Thonberg, H, Arighi, A, Fenoglio, C, Scarpini, E, Fumagalli, G, Cope, T, Timberlake, C, Rittman, T, Shoesmith, C, Bartha, R, Rademakers, R, Wilke, C, Karnarth, HO, Bender, B, Bruffaerts, R, Vandamme, P, Vandenbulcke, M, Ferreira, CB, Miltenberger, G, Maruta Mpsych, C, Verdelho, A, Afonso, S, Taipa, R, Caroppo, P, Di Fede, G, Giaccone, G, Muscio, C, Prioni, S, Redaelli, V, Rossi, G, Tiraboschi, P, Duro Npsych, D, Almeida, M R, Castelo-Branco, M, Leitão, MJ, Tabuas-Pereira, M, Santiago, B, Gauthier, S, Rosa-Neto, P, Veldsman, M, Thompson, P, Langheinrich, T, Prix, C, Hoegen, T, Wlasich, E, Loosli, S, Schonecker, S, Semler, E, Anderl-Straub, S, Russell, LL, Greaves, CV, Bocchetta, M, Nicholas, J, Convery, RS, Moore, K, Cash, DM, van Swieten, J.C., Jiskoot, Lize, Moreno, F, Sanchez-Valle, R, Borroni, B, Laforce, R, Jr, Masellis, M, Tartaglia, MC, Graff, C, Rotondo, E, Galimberti, D, Rowe, JB, Finger, E, Synofzik, M, Vandenberghe, R, Mendonça, A, Tagliavini, F, Santana, I, Ducharme, S, Butler, C, Gerhard, A, Levin, J, Danek, A, Otto, M, Warren, JD, Rohrer, JD, Rossor, MN, Fox, NC, Woollacott, IOC, Shafei, R, Heller, C, Guerreiro, R, Bras, J, Thomas, DL, Mead, S, Meeter, Lieke, Panman, J, Papma, J, Poos, J, van Minkelen, Rick, Al Pijnenburg, Y, Barandiaran, M, Indakoetxea, B, Gabilondo, A, Tainta, M, de Arriba, M, Gorostidi, A, Zulaica, M, Villanua, J, Diaz, Z, Borrego-Ecija, S, Olives, J, Lladó, A, Balasa, M, Antonell, A, Bargallo, N, Premi, E, Cosseddu Mpsych, M, Gazzina, S, Padovani, A, Gasparotti, R, Archetti, S, Black, S, Mitchell, S, Rogaeva, E, Freedman, M, Keren, R, Tang-Wai, D, Öijerstedt, L, Andersson, C, Jelic, V, Thonberg, H, Arighi, A, Fenoglio, C, Scarpini, E, Fumagalli, G, Cope, T, Timberlake, C, Rittman, T, Shoesmith, C, Bartha, R, Rademakers, R, Wilke, C, Karnarth, HO, Bender, B, Bruffaerts, R, Vandamme, P, Vandenbulcke, M, Ferreira, CB, Miltenberger, G, Maruta Mpsych, C, Verdelho, A, Afonso, S, Taipa, R, Caroppo, P, Di Fede, G, Giaccone, G, Muscio, C, Prioni, S, Redaelli, V, Rossi, G, Tiraboschi, P, Duro Npsych, D, Almeida, M R, Castelo-Branco, M, Leitão, MJ, Tabuas-Pereira, M, Santiago, B, Gauthier, S, Rosa-Neto, P, Veldsman, M, Thompson, P, Langheinrich, T, Prix, C, Hoegen, T, Wlasich, E, Loosli, S, Schonecker, S, Semler, E, and Anderl-Straub, S

Published
2020

9. The Italian dementia with Lewy bodies study group (DLB-SINdem): toward a standardization of clinical procedures and multicenter cohort studies design

Author

Bonanni, L, Cagnin, A., Agosta, F., Babiloni, C., Borroni, B., Bozzali, M., Bruni, A. C., Filippi, M., Galimberti, D., Monastero, R., Muscio, C., Parnetti, L., Perani, D., Serra, L., Silani, V., Tiraboschi, P., Padovani, A., On behalf of DLB SINdem study group, Null, Alberici, A., Alberoni, M., Amici, S., Appollonio, I., Arena, M. G., Arighi, A., Avanzi, S., Bagella, C. F., Baglio, F., Barocco, F., Belardinelli, N., Bonuccelli, U., Bottini, G., Bruno Bossio, R., Bruno, G., Buccomino, D., Cacchiò, G., Calabrese, E., Campanelli, A., Canevelli, M., Canu, E. D. G., Cappa, A., Capra, C., Carapelle, E., Caratozzolo, S., Carbone, G. F. S., Cattaruzza, T., Cerami, C., Cester, A., Cheldi, A., Cherchi, R., Chiari, A., Cirafisi, C., Colao, R., Confaloni, A., Conti, M. Z., Costa, A., Costa, B., Cotelli, M. S., Cova, I., Cravello, L., Cumbo, E., Cupidi, C., De Togni, L., Del Din, G., Del Re, M. L., Dentizzi, C., Di Lorenzo, F., Di Stefano, F., Dikova, N., Farina, E., Floris, G., Foti, A., Franceschi, M., Fumagalli, G. G., Gabelli, C., Ghidoni, E., Giannandrea, D., Giordana, M. T., Giorelli, M., Giubilei, F., Grimaldi, L., Grimaldi, R., Guglielmi, V., Lanari, A., Le Pira, F., Letteri, F., Levi Minzi, G. V., Lorusso, S., Ludovico, L., Luzzi, S., Maggiore, L., Magnani, G., Mancini, G., Manconi, F. M., Manfredi, L., Maniscalco, M., Marano, P., Marcon, M., Marcone, A., Marra, C., Martorana, A., Mascia, M. G., Mascia, V., Mauri, M., Mazzei, B., Meloni, M., Merlo, P., Messa, G., Milia, A., Monacelli, F., Montecalvo, G., Moschella, V., Mura, G., Nemni, R., Nobili, F., Notarelli, A., Di Giacomo, R., Onofrj, M., Paci, C., Padiglioni, C., Perini, M., Perotta, D., Perri, Formenti A., Perri, R., Piccininni, C., Piccoli, T., Pilia, G., Pilotto, A., Poli, S., Pomati, S., Pompanin, S., Pucci, E., Puccio, G., Quaranta, D., Rainero, I., Rea, G., Realmuto, S., Riva, M., Rizzetti, M. C., Rolma, G., Rozzini, L., Sacco, L., Saibene, F. L., Scarpini, E., Sensi, S., Seripa, D., Sinforiani, E., Sorbi, S., Sorrentino, Giuseppe, Spallazzi, M., Stracciari, A., Talarico, G., Tassinari, T., Thomas, A., Tiezzi, A., Tomassini, P. F., Trebbastoni, A., Tremolizzo, L., Tripi, G., Ursini, F., Vaianella, L., Valluzzi, F., Vezzadini, G., Vista, M., Volontè, M. A., Bonanni, L, Cagnin, A, Agosta, F, Babiloni, C, Borroni, B, Bozzali, M, Bruni, A, Filippi, M, Galimberti, D, Monastero, R, Muscio, C, Parnetti, L, Perani, D, Serra, L, Silani, V, Tiraboschi, P, Padovani, A, Alberici, A, Alberoni, M, Amici, S, Appollonio, I, Arena, M, Arighi, A, Avanzi, S, Bagella, C, Baglio, F, Barocco, F, Belardinelli, N, Bonuccelli, U, Bottini, G, Bruno Bossio, R, Bruno, G, Buccomino, D, Cacchiò, G, Calabrese, E, Campanelli, A, Canevelli, M, Canu, E, Cappa, A, Capra, C, Carapelle, E, Caratozzolo, S, Carbone, G, Cattaruzza, T, Cerami, C, Cester, A, Cheldi, A, Cherchi, R, Chiari, A, Cirafisi, C, Colao, R, Confaloni, A, Conti, M, Costa, A, Costa, B, Cotelli, M, Cova, I, Cravello, L, Cumbo, E, Cupidi, C, de Togni, L, Del Din, G, Del Re, M, Dentizzi, C, Di Lorenzo, F, Di Stefano, F, Dikova, N, Farina, E, Floris, G, Foti, A, Franceschi, M, Fumagalli, G, Gabelli, C, Ghidoni, E, Giannandrea, D, Giordana, M, Giorelli, M, Giubilei, F, Grimaldi, L, Grimaldi, R, Guglielmi, V, Lanari, A, Le Pira, F, Letteri, F, Levi Minzi, G, Lorusso, S, Ludovico, L, Luzzi, S, Maggiore, L, Magnani, G, Mancini, G, Manconi, F, Manfredi, L, Maniscalco, M, Marano, P, Marcon, M, Marcone, A, Marra, C, Martorana, A, Mascia, M, Mascia, V, Mauri, M, Mazzei, B, Meloni, M, Merlo, P, Messa, G, Milia, A, Monacelli, F, Montecalvo, G, Moschella, V, Mura, G, Nemni, R, Nobili, F, Notarelli, A, Di Giacomo, R, Onofrj, M, Paci, C, Padiglioni, C, Perini, M, Perotta, D, Perri, F, Perri, R, Piccininni, C, Piccoli, T, Pilia, G, Pilotto, A, Poli, S, Pomati, S, Pompanin, S, Pucci, E, Puccio, G, Quaranta, D, Rainero, I, Rea, G, Realmuto, S, Riva, M, Rizzetti, M, Rolma, G, Rozzini, L, Sacco, L, Saibene, F, Scarpini, E, Sensi, S, Seripa, D, Sinforiani, E, Sorbi, S, Sorrentino, G, Spallazzi, M, Stracciari, A, Talarico, G, Tassinari, T, Thomas, A, Tiezzi, A, Tomassini, P, Trebbastoni, A, Tremolizzo, L, Tripi, G, Ursini, F, Vaianella, L, Valluzzi, F, Vezzadini, G, Vista, M, Volontè, M, Bruni, Ac, DLB-SINdem study, Group, Bruni, AC, and Padovani, A - On behalf of DLB-SINdem study group

Subjects
Lewy Body Disease, medicine.medical_specialty, Pediatrics, Dementia with Lewy bodie, Dementia with Lewy bodies, Dermatology, Cohort Studies, Diagnosis, Differential, 03 medical and health sciences, 0302 clinical medicine, Quality of life, Alzheimer Disease, Surveys and Questionnaires, mental disorders, Standardization of diagnostic procedures, Diagnosis, Survey, Disease Management, Humans, Italy, Research Design, 2708, Neurology (clinical), Psychiatry and Mental Health, medicine, Dementia, 030212 general & internal medicine, MED/01 - STATISTICA MEDICA, MED/26 - NEUROLOGIA, business.industry, Standardization of diagnostic procedure, General Medicine, medicine.disease, Settore MED/26 - NEUROLOGIA, Cohort, Differential, Physical therapy, Delirium, Alzheimer's disease, medicine.symptom, business, 030217 neurology & neurosurgery, Frontotemporal dementia, Cohort study
Abstract

Dementia with Lewy bodies (DLB) causes elevated outlays for the National Health Systems due to high institutionalization rate and patients' reduced quality of life and high mortality. Furthermore, DLB is often misdiagnosed as Alzheimer's disease. These data motivate harmonized multicenter longitudinal cohort studies to improve clinical management and therapy monitoring. The Italian DLB study group of the Italian Neurological Society for dementia (SINdem) developed and emailed a semi-structured questionnaire to 572 national dementia centers (from primary to tertiary) to prepare an Italian large longitudinal cohort. The questionnaire surveyed: (1) prevalence and incidence of DLB; (2) clinical assessment; (3) relevance and availability of diagnostic tools; (4) pharmacological management of cognitive, motor, and behavioural disturbances; (5) causes of hospitalization, with specific focus on delirium and its treatment. Overall, 135 centers (23.6 %) contributed to the survey. Overall, 5624 patients with DLB are currently followed by the 135 centers in a year (2042 of them are new patients). The percentage of DLB patients was lower (27 ± 8 %) than that of Alzheimer's disease and frontotemporal dementia (56 ± 27 %) patients. The majority of the centers (91 %) considered the clinical and neuropsychological assessments as the most relevant procedure for a DLB diagnosis. Nonetheless, most of the centers has availability of magnetic resonance imaging (MRI; 95 %), electroencephalography (EEG; 93 %), and FP-CIT single photon emission-computerized tomography (SPECT; 75 %) scan for clinical applications. It will be, therefore, possible to recruit a large harmonized Italian cohort of DLB patients for future cross-sectional and longitudinal multicenter studies.

Published
2017

10. Do beliefs about the pathogenetic role of amyloid affect the interpretation of amyloid PET in the clinic?

Author

Boccardi, M, Altomare, D, Ferrari, C, Festari, C, Antelmi, L, Pievani, M, Tarallo, A, Muscio, C, Guerra, U, Paghera, B, Padovani, A, Frisoni, G, Zanetti, O, Anzola, G, Bertocchi, M, Chito, E, Galluzzi, S, Geroldi, C, Lussignoli, G, Mattioli, F, Moretti, D, Pizzocaro, C, Borroni, B, Rozzini, L, Prelle, A, Gennuso, M, Villani, D, Raimondi, M, Gentile, S, Bellelli, G, Morandi, A, Turco, R, Bellandi, D, Carbone, P, Abruzzi, L, Bettoni, L, Bianchetti, A, Facchi, E, Di Fazio, I, Turla, M, Cotelli, M, Volta, G, Bigni, B, Bilotti, G, Vollaro, S, Rozzini, R, Boffelli, S, Cappuccio, M, Conti, M, Guizzetti, G, Defanti, C, Mirabile, D, Fascendini, S, Manzoni, L, Salvi, G, Belotti, G, Cavaliere, S, Fiacco, F, Valente, L, Ciccone, A, Lanari, A, Selletti, L, Palmerini, F, Avanzi, S, Vezzadini, G, Boccardi M., Altomare D., Ferrari C., Festari C., Antelmi L., Pievani M., Tarallo A., Muscio C., Guerra U. P., Paghera B., Padovani A., Frisoni G. B., Zanetti O., Anzola G. P., Bertocchi M., Chito E., Galluzzi S., Geroldi C., Lussignoli G., Mattioli F., Moretti D., Pizzocaro C., Borroni B., Rozzini L., Prelle A., Gennuso M., Villani D., Raimondi M. C., Gentile S., Bellelli G., Morandi A., Turco R., Bellandi D., Carbone P., Abruzzi L., Bettoni L., Bianchetti A., Facchi E., Di Fazio I., Turla M., Cotelli M. S., Volta G. D., Bigni B., Bilotti G., Vollaro S., Rozzini R., Boffelli S., Cappuccio M., Conti M. Z., Guizzetti G., Defanti C., Mirabile D., Fascendini S., Manzoni L., Salvi G. P., Belotti G., Cavaliere S., Fiacco F., Valente L., Ciccone A., Lanari A., Selletti L., Palmerini F., Avanzi S., Vezzadini G., Boccardi, M, Altomare, D, Ferrari, C, Festari, C, Antelmi, L, Pievani, M, Tarallo, A, Muscio, C, Guerra, U, Paghera, B, Padovani, A, Frisoni, G, Zanetti, O, Anzola, G, Bertocchi, M, Chito, E, Galluzzi, S, Geroldi, C, Lussignoli, G, Mattioli, F, Moretti, D, Pizzocaro, C, Borroni, B, Rozzini, L, Prelle, A, Gennuso, M, Villani, D, Raimondi, M, Gentile, S, Bellelli, G, Morandi, A, Turco, R, Bellandi, D, Carbone, P, Abruzzi, L, Bettoni, L, Bianchetti, A, Facchi, E, Di Fazio, I, Turla, M, Cotelli, M, Volta, G, Bigni, B, Bilotti, G, Vollaro, S, Rozzini, R, Boffelli, S, Cappuccio, M, Conti, M, Guizzetti, G, Defanti, C, Mirabile, D, Fascendini, S, Manzoni, L, Salvi, G, Belotti, G, Cavaliere, S, Fiacco, F, Valente, L, Ciccone, A, Lanari, A, Selletti, L, Palmerini, F, Avanzi, S, Vezzadini, G, Boccardi M., Altomare D., Ferrari C., Festari C., Antelmi L., Pievani M., Tarallo A., Muscio C., Guerra U. P., Paghera B., Padovani A., Frisoni G. B., Zanetti O., Anzola G. P., Bertocchi M., Chito E., Galluzzi S., Geroldi C., Lussignoli G., Mattioli F., Moretti D., Pizzocaro C., Borroni B., Rozzini L., Prelle A., Gennuso M., Villani D., Raimondi M. C., Gentile S., Bellelli G., Morandi A., Turco R., Bellandi D., Carbone P., Abruzzi L., Bettoni L., Bianchetti A., Facchi E., Di Fazio I., Turla M., Cotelli M. S., Volta G. D., Bigni B., Bilotti G., Vollaro S., Rozzini R., Boffelli S., Cappuccio M., Conti M. Z., Guizzetti G., Defanti C., Mirabile D., Fascendini S., Manzoni L., Salvi G. P., Belotti G., Cavaliere S., Fiacco F., Valente L., Ciccone A., Lanari A., Selletti L., Palmerini F., Avanzi S., and Vezzadini G.

Abstract

Background: Beliefs of dementia experts about the pathogenic role of amyloid in Alzheimer's disease (AD) may affect the use of amyloid positron emission tomography (PET). Objective:To assess the role attributed to amyloid in AD pathogenesis by Italian dementia experts, and whether this modulates the impact of amyloid PET results in their diagnostic workup. Methods: 22 dementia experts rated their beliefs about the pathogenic role of amyloid. Then, we asked them to rate the probability of change in diagnosis based on the result of amyloid PET for 7 case vignettes, depicting patients who initially received a diagnosis based on a comprehensive workup and later received amyloid PET results consistent or inconsistent with the clinical picture. Results: 55% of the experts assigned a dominant role to amyloid, and 32% attributed a similar role to amyloid and tau in AD pathogenesis. The probability of change in diagnosis ranged from 17% (SD = 21.6) for cases with consistent to 51% (SD = 34) for cases with inconsistent PET versus clinical data. Diagnostic change was not biased by the clinicians' beliefs about AD pathogenesis. Conclusions: This work supports an unbiased interpretation of amyloid PET across different beliefs about the pathogenic role of amyloid, and a belief -independent reluctance to change diagnosis in cases where change is expected and recommended. (C) 2015 S. Karger AG, Basel

Published
2016

11. Assessment of the incremental diagnostic value of florbetapir F 18 imaging in patients with cognitive impairment: The incremental diagnostic value of amyloid PET with [18F]-florbetapir (INDIA-FBP) study

Author

Boccardi, M, Altomare, D, Ferrari, C, Festari, C, Guerra, U, Paghera, B, Pizzocaro, C, Lussignoli, G, Geroldi, C, Zanetti, O, Cotelli, M, Turla, M, Borroni, B, Rozzini, L, Mirabile, D, Defanti, C, Gennuso, M, Prelle, A, Gentile, S, Morandi, A, Vollaro, S, Volta, G, Bianchetti, A, Conti, M, Cappuccio, M, Carbone, P, Bellandi, D, Abruzzi, L, Bettoni, L, Villani, D, Raimondi, M, Lanari, A, Ciccone, A, Facchi, E, Di Fazio, I, Rozzini, R, Boffelli, S, Manzoni, L, Salvi, G, Cavaliere, S, Belotti, G, Avanzi, S, Pasqualetti, P, Muscio, C, Padovani, A, Frisoni, G, Antelmi, L, Galluzzi, S, Pievani, M, Redolfi, A, Tarallo, A, Arora, A, Bertocchi, M, Chito, E, Moretti, D, Giubbini, R, Rodella, C, Camoni, L, Massetti, V, Andreoli, M, Bellelli, G, Fascendini, S, Mattioli, F, Turco, R, Vezzadini, G, Raimondi, V, Mondini, S, Zanacchi, E, Grigolo, M, Pezzini, A, Bilotti, G, Bigni, B, Zavarise, P, Ngonga, G, Anzola, G, Turrone, R, Guizzetti, G, Zanetti, M, Boccardi M., Altomare D., Ferrari C., Festari C., Guerra U. P., Paghera B., Pizzocaro C., Lussignoli G., Geroldi C., Zanetti O., Cotelli M. S., Turla M., Borroni B., Rozzini L., Mirabile D., Defanti C., Gennuso M., Prelle A., Gentile S., Morandi A., Vollaro S., Volta G. D., Bianchetti A., Conti M. Z., Cappuccio M., Carbone P., Bellandi D., Abruzzi L., Bettoni L., Villani D., Raimondi M. C., Lanari A., Ciccone A., Facchi E., Di Fazio I., Rozzini R., Boffelli S., Manzoni L., Salvi G. P., Cavaliere S., Belotti G., Avanzi S., Pasqualetti P., Muscio C., Padovani A., Frisoni G. B., Antelmi L., Galluzzi S., Pievani M., Redolfi A., Tarallo A., Arora A., Bertocchi M., Chito E., Moretti D. V., Giubbini R., Rodella C., Camoni L., Massetti V., Andreoli M., Bellelli G., Fascendini S., Mattioli F., Turco R., Vezzadini G., Raimondi V., Mondini S., Zanacchi E. C., Grigolo M., Pezzini A., Bilotti G., Bigni B., Zavarise P., Ngonga G., Anzola G. P., Turrone R., Guizzetti G., Zanetti M., Boccardi, M, Altomare, D, Ferrari, C, Festari, C, Guerra, U, Paghera, B, Pizzocaro, C, Lussignoli, G, Geroldi, C, Zanetti, O, Cotelli, M, Turla, M, Borroni, B, Rozzini, L, Mirabile, D, Defanti, C, Gennuso, M, Prelle, A, Gentile, S, Morandi, A, Vollaro, S, Volta, G, Bianchetti, A, Conti, M, Cappuccio, M, Carbone, P, Bellandi, D, Abruzzi, L, Bettoni, L, Villani, D, Raimondi, M, Lanari, A, Ciccone, A, Facchi, E, Di Fazio, I, Rozzini, R, Boffelli, S, Manzoni, L, Salvi, G, Cavaliere, S, Belotti, G, Avanzi, S, Pasqualetti, P, Muscio, C, Padovani, A, Frisoni, G, Antelmi, L, Galluzzi, S, Pievani, M, Redolfi, A, Tarallo, A, Arora, A, Bertocchi, M, Chito, E, Moretti, D, Giubbini, R, Rodella, C, Camoni, L, Massetti, V, Andreoli, M, Bellelli, G, Fascendini, S, Mattioli, F, Turco, R, Vezzadini, G, Raimondi, V, Mondini, S, Zanacchi, E, Grigolo, M, Pezzini, A, Bilotti, G, Bigni, B, Zavarise, P, Ngonga, G, Anzola, G, Turrone, R, Guizzetti, G, Zanetti, M, Boccardi M., Altomare D., Ferrari C., Festari C., Guerra U. P., Paghera B., Pizzocaro C., Lussignoli G., Geroldi C., Zanetti O., Cotelli M. S., Turla M., Borroni B., Rozzini L., Mirabile D., Defanti C., Gennuso M., Prelle A., Gentile S., Morandi A., Vollaro S., Volta G. D., Bianchetti A., Conti M. Z., Cappuccio M., Carbone P., Bellandi D., Abruzzi L., Bettoni L., Villani D., Raimondi M. C., Lanari A., Ciccone A., Facchi E., Di Fazio I., Rozzini R., Boffelli S., Manzoni L., Salvi G. P., Cavaliere S., Belotti G., Avanzi S., Pasqualetti P., Muscio C., Padovani A., Frisoni G. B., Antelmi L., Galluzzi S., Pievani M., Redolfi A., Tarallo A., Arora A., Bertocchi M., Chito E., Moretti D. V., Giubbini R., Rodella C., Camoni L., Massetti V., Andreoli M., Bellelli G., Fascendini S., Mattioli F., Turco R., Vezzadini G., Raimondi V., Mondini S., Zanacchi E. C., Grigolo M., Pezzini A., Bilotti G., Bigni B., Zavarise P., Ngonga G., Anzola G. P., Turrone R., Guizzetti G., and Zanetti M.

Abstract

IMPORTANCE Cerebral amyloidosis is a key abnormality in Alzheimer disease (AD) and can be detected in vivo with positron emission tomography (PET) ligands. Although amyloid PET has clearly demonstrated analytical validity, its clinical utility is debated. OBJECTIVE To evaluate the incremental diagnostic value of amyloid PET with florbetapir F 18 in addition to the routine clinical diagnostic assessment of patients evaluated for cognitive impairment. DESIGN, SETTING, AND PARTICIPANTS The Incremental Diagnostic Value ofAmyloid PET With [18F]-Florbetapir (INDIA-FBP) Study is a multicenter study involving 18 AD evaluation units from eastern Lombardy, Northern Italy, 228 consecutive adults with cognitive impairmentwere evaluated for AD and other causes of cognitive decline, with a prescan diagnostic confidence of AD between 15%and 85%. Participants underwent routine clinical and instrumental diagnostic assessment. A prescan diagnosiswas made, diagnostic confidencewas estimated, and drug treatmentwas provided. At the time of thisworkup, an amyloid PET/computed tomographic scanwas performed, and the resultwas communicated to physicians afterworkup completion. Physicianswere asked to review the diagnosis, diagnostic confidence, and treatment after the scan. The studywas conducted from August 5, 2013, to December 31, 2014. MAIN OUTCOMES AND MEASURES Primary outcomeswere prescan to postscan changes of diagnosis, diagnostic confidence, and treatment. RESULTS Of the 228 participants, 107 (46%) were male; mean (SD) age was 70.5 (7) years. Diagnostic change occurred in 46 patients (79%) having both a previous diagnosis of AD and an amyloid-negative scan (P < .001) and in 16 (53%) of those with non-AD diagnoses and an amyloid-positive scan (P < .001). Diagnostic confidence in AD diagnosis increased by 15.2%in amyloid-positive (P < .001; effect size Cohen d = 1.04) and decreased by 29.9%in amyloid-negative (P < .001; d = -1.19) scans. Acetylcholinesterase inhibitors and

Published
2016

12. Efficacy of an Italian psychosocial intervention for caregivers of Alzheimer’s patients

Author

Muscio, C, Tiraboschi, P, Chitò, E, Nicoli, P, Sala, M, Greco, A, Ciampichini, R, Zucchi, A, Defanti, C, Defanti, CA, SALA, MARTA, GRECO, ANDREA, CIAMPICHINI, ROBERTA, Muscio, C, Tiraboschi, P, Chitò, E, Nicoli, P, Sala, M, Greco, A, Ciampichini, R, Zucchi, A, Defanti, C, Defanti, CA, SALA, MARTA, GRECO, ANDREA, and CIAMPICHINI, ROBERTA

Published
2015

13. Impact of alcohol consumption in healthy adults: a magnetic resonance imaging investigation

Author

Preti, A, Muscio, C, Boccardi, M, Lorenzi, M, De Girolamo, Giovanni, Frisoni, G., Preti, A, Muscio, C, Boccardi, M, Lorenzi, M, De Girolamo, Giovanni, and Frisoni, G.

Abstract

The impact of alcohol on brain morphology was studied in a large group of cognitively intact people whose consumption of alcohol was below the threshold for abuse. Participants were 367 healthy subjects, aged 18 years or older, who underwent magnetic resonance imaging (MRI) for reasons other than cognitive impairment. MRI analyses were carried out using SPM8 software on the MATLAB 7.9 platform. Gray matter (GM) and white matter (WM) volumes were normalized for intracranial volume. Participants were interviewed about their lifetime consumption of alcohol, nicotine and other available illicit substances. Direct WM and GM comparisons between alcohol users and non-users did not detect significant differences. Differences also did not emerge from multiple regression analyses or in the subgroup aged 65 or older. Based on this study's findings, we cannot infer a detrimental effect of alcohol on the brain of normal adults. These data may be considered to provide reference information for clinical studies.

Published
2014

16. Italian consensus recommendations for a biomarker‐based aetiological diagnosis in mild cognitive impairment patients

Author

Cristina Festari, Valentina Nicolosi, Orazio Schillaci, Pietro Tiraboschi, G. Salvini Porro, Giuseppe Sancesario, Fabrizio Tagliavini, Francesca B. Pizzini, Daniela Perani, Andrea Falini, A. Beltramello, A. Padovani, Flavio Nobili, Marina Boccardi, Davide Chiasserini, M. Trabucchi, Angelo Bianchetti, Ugo Paolo Guerra, Lucilla Parnetti, Stefano F. Cappa, Cristina Muscio, Giovanni B. Frisoni, S. Morbelli, Marcello Ciaccio, Boccardi, M., Nicolosi, V., Festari, C., Bianchetti, A., Cappa, S., Chiasserini, D., Falini, A., Guerra, U. P., Nobili, F., Padovani, A., Sancesario, G., Morbelli, S., Parnetti, L., Tiraboschi, P., Muscio, C., Perani, D., Pizzini, F. B., Beltramello, A., Salvini Porro, G., Ciaccio, M., Schillaci, O., Trabucchi, M., Tagliavini, F., Frisoni, G. B., Boccardi M., Nicolosi V., Festari C., Bianchetti A., Cappa S., Chiasserini D., Falini A., Guerra U.P., Nobili F., Padovani A., Sancesario G., Morbelli S., Parnetti L., Tiraboschi P., Muscio C., Perani D., Pizzini F.B., Beltramello A., Salvini Porro G., Ciaccio M., Schillaci O., Trabucchi M., Tagliavini F., and Frisoni G.B.

Subjects
Pediatrics, medicine.medical_specialty, Neurology, Consensus, diagnosis, biomarker-based diagnosis, 03 medical and health sciences, 0302 clinical medicine, Alzheimer Disease, medicine, Humans, Cognitive Dysfunction, 030212 general & internal medicine, implementation, Neuroradiology, biomarker-based diagnosi, consensus recommendation, Dementia with Lewy bodies, business.industry, Parkinsonism, Brain, Frontotemporal lobar degeneration, medicine.disease, Magnetic Resonance Imaging, diagnostic algorithm, MCI, diagnosi, consensus recommendations, Italy, multiple biomarkers, Positron-Emission Tomography, Etiology, Biomarker (medicine), biomarker, Neurology (clinical), business, Neurocognitive, Alzheimer’s disease, 030217 neurology & neurosurgery, Biomarkers
Abstract

Background and purpose: Biomarkers support the aetiological diagnosis of neurocognitive disorders in vivo. Incomplete evidence is available to drive clinical decisions; available diagnostic algorithms are generic and not very helpful in clinical practice. The aim was to develop a biomarker-based diagnostic algorithm for mild cognitive impairment patients, leveraging on knowledge from recognized national experts. Methods: With a Delphi procedure, experienced clinicians making variable use of biomarkers in clinical practice and representing five Italian scientific societies (neurology – Società Italiana di Neurologia per le Demenze; neuroradiology – Associazione Italiana di Neuroradiologia; biochemistry – Società Italiana di Biochimica Clinica; psychogeriatrics – Associazione Italiana di Psicogeriatria; nuclear medicine – Associazione Italiana di Medicina Nucleare) defined the theoretical framework, relevant literature, the diagnostic issues to be addressed and the diagnostic algorithm. An N–1 majority defined consensus achievement. Results: The panellists chose the 2011 National Institute on Aging and Alzheimer's Association diagnostic criteria as the reference theoretical framework and defined the algorithm in seven Delphi rounds. The algorithm includes baseline clinical and cognitive assessment, blood examination, and magnetic resonance imaging with exclusionary and inclusionary roles; dopamine transporter single-photon emission computed tomography (if no/unclear parkinsonism) or metaiodobenzylguanidine cardiac scintigraphy for suspected dementia with Lewy bodies with clear parkinsonism (round VII, votes(yes-no-abstained): 3-1-1); 18F-fluorodeoxyglucose positron emission tomography for suspected frontotemporal lobar degeneration and low diagnostic confidence of Alzheimer’s disease (round VII, 4-0-1); cerebrospinal fluid for suspected Alzheimer’s disease (round IV, 4-1-0); and amyloid positron emission tomography if cerebrospinal fluid was not possible/accepted (round V, 4-1-0) or inconclusive (round VI, 5-0-0). Conclusions: These consensus recommendations can guide clinicians in the biomarker-based aetiological diagnosis of mild cognitive impairment, whilst guidelines cannot be defined with evidence-to-decision procedures due to incomplete evidence.

Published
2019

17. Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre–Mild Cognitive Impairment

Author

Tondo, Giacomo, Boccalini, Cecilia, Vanoli, Emilia Giovanna, Presotto, Luca, Muscio, Cristina, Ciullo, Valentina, Banaj, Nerisa, Piras, Federica, Filippini, Graziella, Tiraboschi, Pietro, Tagliavini, Fabrizio, Frisoni, Giovanni Battista, Cappa, Stefano F., Spalletta, Gianfranco, Perani, Daniela, Tondo, G, Boccalini, C, Vanoli, E, Presotto, L, Muscio, C, Ciullo, V, Banaj, N, Piras, F, Filippini, G, Tiraboschi, P, Tagliavini, F, Frisoni, G, Cappa, S, Spalletta, G, and Perani, D

Subjects
imaging, Neurology (clinical), Research Article
Abstract

Background and ObjectiveThis was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre–mild cognitive impairment [pre–MCI]).MethodsData were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism.ResultsA total of 105 participants (SCD = 49, pre–MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions.DiscussionFDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre–MCI. These results indicate that SCD and pre–MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.

Published
2022
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18. Assessment of the incremental diagnostic value of florbetapir F 18 imaging in patients with cognitive impairment: The incremental diagnostic value of amyloid PET with [ 18 F]-florbetapir (INDIA-FBP) study

Author

Boccardi, Marina, Altomare, Daniele, Ferrari, Clarissa, Festari, Cristina, Guerra, Ugo Paolo, Paghera, Barbara, Pizzocaro, Claudio, Lussignoli, Giulia, Geroldi, Cristina, Zanetti, Orazio, Cotelli, Maria Sofia, Turla, Marinella, Borroni, Barbara, Rozzini, Luca, Mirabile, Dario, Defanti, Carlo, Gennuso, Michele, Prelle, Alessandro, Gentile, Simona, Morandi, Alessandro, Vollaro, Stefano, Volta, Giorgio Dalla, Bianchetti, Angelo, Conti, Marta Zaffira, Cappuccio, Melania, Carbone, Pasqualina, Bellandi, Daniele, Abruzzi, Luciano, Bettoni, Luigi, Villani, Daniele, Raimondi, Maria Clara, Lanari, Alessia, Ciccone, Alfonso, Facchi, Emanuela, Di Fazio, Ignazio, Rozzini, Renzo, Boffelli, Stefano, Manzoni, Laura, Salvi, Giovanni Pietro, Cavaliere, Sabina, Belotti, Gloria, Avanzi, Stefano, Pasqualetti, Patrizio, Muscio, Cristina, Padovani, Alessandro, Frisoni, Giovanni B., Antelmi, Luigi, Galluzzi, Samantha, Pievani, Michela, Redolfi, Alberto, Tarallo, ANNA ROSA, Arora, Anupa, Bertocchi, Monica, Chitò, Eugenia, Moretti, Davide V., Giubbini, Raffaele, Rodella, Carlo, Camoni, Luca, Massetti, Valentina, Andreoli, Michela, Bellelli, Giuseppe, Fascendini, Sara, Mattioli, Flavia, Turco, Renato, Vezzadini, Giuliana, Raimondi, Vanessa, Mondini, Sara, Zanacchi, Elisa Carolina, Grigolo, Marta, Pezzini, Alessandra, Bilotti, Giacinta, Bigni, Barbara, Zavarise, Paola, Ngonga, Gael, Anzola, Gian Paolo, Turrone, Rosanna, Guizzetti, Gianluca, Zanetti, Marina, Boccardi, Marina, Altomare, Daniele, Ferrari, Clarissa, Festari, Cristina, Frisoni, Giovanni, Boccardi, M, Altomare, D, Ferrari, C, Festari, C, Guerra, U, Paghera, B, Pizzocaro, C, Lussignoli, G, Geroldi, C, Zanetti, O, Cotelli, M, Turla, M, Borroni, B, Rozzini, L, Mirabile, D, Defanti, C, Gennuso, M, Prelle, A, Gentile, S, Morandi, A, Vollaro, S, Volta, G, Bianchetti, A, Conti, M, Cappuccio, M, Carbone, P, Bellandi, D, Abruzzi, L, Bettoni, L, Villani, D, Raimondi, M, Lanari, A, Ciccone, A, Facchi, E, Di Fazio, I, Rozzini, R, Boffelli, S, Manzoni, L, Salvi, G, Cavaliere, S, Belotti, G, Avanzi, S, Pasqualetti, P, Muscio, C, Padovani, A, Frisoni, G, Antelmi, L, Galluzzi, S, Pievani, M, Redolfi, A, Tarallo, A, Arora, A, Bertocchi, M, Chito, E, Moretti, D, Giubbini, R, Rodella, C, Camoni, L, Massetti, V, Andreoli, M, Bellelli, G, Fascendini, S, Mattioli, F, Turco, R, Vezzadini, G, Raimondi, V, Mondini, S, Zanacchi, E, Grigolo, M, Pezzini, A, Bilotti, G, Bigni, B, Zavarise, P, Ngonga, G, Anzola, G, Turrone, R, Guizzetti, G, and Zanetti, M

Subjects
Male, medicine.medical_specialty, Positron-Emission Tomography/methods/standards, Aged, Aged, 80 and over, Alzheimer Disease, Amyloid beta-Peptides, Cognitive Dysfunction, Female, Humans, Male, Positron-Emission Tomography, Predictive Value of Tests, Aniline Compounds, Ethylene Glycols, 030218 nuclear medicine & medical imaging, 03 medical and health sciences, ddc:616.89, 0302 clinical medicine, Alzheimer Disease, Predictive Value of Tests, Medical imaging, 80 and over, Medicine, Humans, Cognitive Dysfunction, Cognitive decline, Cognitive impairment, Amyloid beta-Peptides/metabolism, Aged, Aged, 80 and over, Amyloid beta-Peptides, Aniline Compounds, medicine.diagnostic_test, business.industry, Amyloidosis, Alzheimer Disease/diagnosis/diagnostic imaging/metabolism, Cognitive Dysfunction/diagnosis/diagnostic imaging/metabolism, medicine.disease, aged, aged, 80 and over, alzheimer disease, amyloid beta-peptides, cognitive dysfunction, female, humans, male, positron-emission tomography, predictive value of tests, aniline compounds, ethylene glycols, Surgery, Female, Positron-Emission Tomography, Ethylene Glycols, Neurology (clinical), Positron emission tomography, Predictive value of tests, Radiology, Alzheimer's disease, Abnormality, business, 030217 neurology & neurosurgery
Abstract

IMPORTANCE Cerebral amyloidosis is a key abnormality in Alzheimer disease (AD) and can be detected in vivo with positron emission tomography (PET) ligands. Although amyloid PET has clearly demonstrated analytical validity, its clinical utility is debated. OBJECTIVE To evaluate the incremental diagnostic value of amyloid PET with florbetapir F 18 in addition to the routine clinical diagnostic assessment of patients evaluated for cognitive impairment. DESIGN, SETTING, AND PARTICIPANTS The Incremental Diagnostic Value ofAmyloid PET With [18F]-Florbetapir (INDIA-FBP) Study is a multicenter study involving 18 AD evaluation units from eastern Lombardy, Northern Italy, 228 consecutive adults with cognitive impairmentwere evaluated for AD and other causes of cognitive decline, with a prescan diagnostic confidence of AD between 15%and 85%. Participants underwent routine clinical and instrumental diagnostic assessment. A prescan diagnosiswas made, diagnostic confidencewas estimated, and drug treatmentwas provided. At the time of thisworkup, an amyloid PET/computed tomographic scanwas performed, and the resultwas communicated to physicians afterworkup completion. Physicianswere asked to review the diagnosis, diagnostic confidence, and treatment after the scan. The studywas conducted from August 5, 2013, to December 31, 2014. MAIN OUTCOMES AND MEASURES Primary outcomeswere prescan to postscan changes of diagnosis, diagnostic confidence, and treatment. RESULTS Of the 228 participants, 107 (46%) were male; mean (SD) age was 70.5 (7) years. Diagnostic change occurred in 46 patients (79%) having both a previous diagnosis of AD and an amyloid-negative scan (P < .001) and in 16 (53%) of those with non-AD diagnoses and an amyloid-positive scan (P < .001). Diagnostic confidence in AD diagnosis increased by 15.2%in amyloid-positive (P < .001; effect size Cohen d = 1.04) and decreased by 29.9%in amyloid-negative (P < .001; d = -1.19) scans. Acetylcholinesterase inhibitors and memantine hydrochloride were introduced in 61 (65.6%) patients with positive scan results who had not previously received those drugs, and the use of the drugs was discontinued in 6 (33.3%) patients with negative scan results who were receiving those drugs (P < .001). CONCLUSIONS AND RELEVANCE Amyloid PET in addition to routine assessment in patients with cognitive impairment has a significant effect on diagnosis, diagnostic confidence, and drug treatment. The effect on health outcomes, such as morbidity and mortality, remains to be assessed.

Published
2016

20. Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA.

Author

De Francesco S, Crema C, Archetti D, Muscio C, Reid RI, Nigri A, Bruzzone MG, Tagliavini F, Lodi R, D'Angelo E, Boeve B, Kantarci K, Firbank M, Taylor JP, Tiraboschi P, and Redolfi A

Subjects
Humans, Diagnosis, Differential, Biomarkers, Machine Learning, Algorithms, Magnetic Resonance Imaging methods, Alzheimer Disease diagnostic imaging, Alzheimer Disease pathology
Abstract

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis., (© 2023. Springer Nature Limited.)

Published
2023
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21. Correction: Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I‑UDSNB 1.0): development and normative data.

Author

Conca F, Esposito V, Rundo F, Quaranta D, Muscio C, Manenti R, Caruso G, Lucca U, Galbussera AA, Di Tella S, Baglio F, L'Abbate F, Canu E, Catania V, Filippi M, Mattavelli G, Poletti B, Silani V, Lodi R, De Matteis M, Maserati MS, Arighi A, Rotondo E, Tanzilli A, Pace A, Garramone F, Cavaliere C, Pardini M, Rizzetto C, Sorbi S, Perri R, Tiraboschi P, Canessa N, Cotelli M, Ferri R, Weintraub S, Marra C, Tagliavini F, Catricalà E, and Cappa SF

Published
2023
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22. Educational interventions to improve detection and management of cognitive decline in primary care-An Italian multicenter pragmatic study.

Author

Lombardi G, Chipi E, Arenella D, Fiorani A, Frisoni GB, Linarello S, Montanucci C, Muscio C, Pacifico I, Pelizzari S, Perani D, Piras F, Rozzini L, Sorbi S, Spalletta G, Tagliavini F, Tiraboschi P, Parnetti L, and Filippini G

Abstract

Introduction: Timely detection of cognitive decline in primary care is essential to promote an appropriate care pathway and enhance the benefits of interventions. We present the results of a study aimed to evaluate the effectiveness of an educational intervention addressed to Italian family physicians (FPs) to improve timely detection and management of cognitive decline., Materials and Methods: We conducted a pre-post study in six Italian health authorities (HAs) involving 254 FPs and 3,736 patients. We measured process and outcome indicators before the intervention (1 January 2014 to 31 December 2016) and after the intervention (1 January 2018 to 31 December 2019). One interactive face-to-face session workshop was delivered by local cognitive disorders and dementia specialists and FP advisors at each HA, in the period September 2017-December 2017. The session focused on key messages of the local Diagnostic and Therapeutic Care Pathway (DTCP) or regional guidelines: (a) the role of the FP for a timely suspicion of cognitive decline is fundamental; (b) when cognitive decline is suspected, the role of the FP is active in the diagnostic work-up; (c) FP's knowledge on pharmacological and non-pharmacological interventions is essential to improve the management of patients with cognitive decline., Results: An overall improvement in diagnostic procedures and management of patients with cognitive decline by FPs after the intervention was observed. The number of visits per year performed by FPs increased, and the time interval between the first FP consultation and the diagnosis was optimized. Neuroleptic use significantly decreased, whereas the use of benzodiazepines remained steadily high. Non-pharmacological interventions, or use of support services, were underrepresented even in the post-intervention. Differences among the participating HAs were identified and discussed., Discussion: Results from this study suggest the success of the educational intervention addressed to FPs in improving early detection and management of cognitive decline, highlighting the importance to continue medical education in this field. At the same time, further initiatives of care pathway dissemination and implementation should promote strategies to enhance interactions between primary and secondary care optimizing the collaboration between FPs and specialists., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Lombardi, Chipi, Arenella, Fiorani, Frisoni, Linarello, Montanucci, Muscio, Pacifico, Pelizzari, Perani, Piras, Rozzini, Sorbi, Spalletta, Tagliavini, Tiraboschi, Parnetti and Filippini.)

Published
2022
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23. Italian adaptation of the Uniform Data Set Neuropsychological Test Battery (I-UDSNB 1.0): development and normative data.

Author

Conca F, Esposito V, Rundo F, Quaranta D, Muscio C, Manenti R, Caruso G, Lucca U, Galbussera AA, Di Tella S, Baglio F, L'Abbate F, Canu E, Catania V, Filippi M, Mattavelli G, Poletti B, Silani V, Lodi R, De Matteis M, Stanzani Maserati M, Arighi A, Rotondo E, Tanzilli A, Pace A, Garramone F, Cavaliere C, Pardini M, Rizzetto C, Sorbi S, Perri R, Tiraboschi P, Canessa N, Cotelli M, Ferri R, Weintraub S, Marra C, Tagliavini F, Catricalà E, and Cappa SF

Subjects
Humans, Italy, Neuropsychological Tests, Alzheimer Disease diagnosis
Abstract

Background: Neuropsychological testing plays a cardinal role in the diagnosis and monitoring of Alzheimer's disease. A major concern is represented by the heterogeneity of the neuropsychological batteries currently adopted in memory clinics and healthcare centers. The current study aimed to solve this issue., Methods: Following the initiative of the University of Washington's National Alzheimer's Coordinating Center (NACC), we presented the Italian adaptation of the Neuropsychological Test Battery of the Uniform Data Set (I-UDSNB). We collected data from 433 healthy Italian individuals and employed regression models to evaluate the impact of demographic variables on the performance, deriving the reference norms., Results: Higher education and lower age were associated with a better performance in the majority of tests, while sex affected only fluency tests and Digit Span Forward., Conclusions: The I-UDSNB offers a valuable and harmonized tool for neuropsychological testing in Italy, to be used in clinical and research settings., (© 2022. The Author(s).)

Published
2022
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24. Postinfectious Neurologic Complications in COVID-19: A Complex Case Report.

Author

Tiraboschi P, Xhani R, Zerbi SM, Corso A, Martinelli I, Fusi L, Grampa G, Lombardo A, Cavalcante P, Cappelletti C, Andreetta F, Sironi A, Redolfi A, and Muscio C

Subjects
Adult, Brain diagnostic imaging, Female, Fluorodeoxyglucose F18, Humans, Brain Diseases etiology, COVID-19 complications, SARS-CoV-2
Abstract

A 40-y-old woman with severe acute respiratory syndrome coronavirus 2 infection developed neurologic manifestations (confusion, agitation, seizures, dyskinesias, and parkinsonism) a few weeks after the onset of severe acute respiratory syndrome. MRI and cerebrospinal fluid analyses were unremarkable, but 18 F-FDG PET/CT showed limbic and extralimbic hypermetabolism. A full recovery, alongside 18 F-FDG normalization in previously hypermetabolic areas, was observed after intravenous immunoglobulin administration., (© 2021 by the Society of Nuclear Medicine and Molecular Imaging.)

Published
2021
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25. Medical Informatics Platform (MIP): A Pilot Study Across Clinical Italian Cohorts.

Author

Redolfi A, De Francesco S, Palesi F, Galluzzi S, Muscio C, Castellazzi G, Tiraboschi P, Savini G, Nigri A, Bottini G, Bruzzone MG, Ramusino MC, Ferraro S, Gandini Wheeler-Kingshott CAM, Tagliavini F, Frisoni GB, Ryvlin P, Demonet JF, Kherif F, Cappa SF, and D'Angelo E

Abstract

Introduction: With the shift of research focus to personalized medicine in Alzheimer's Dementia (AD), there is an urgent need for tools that are capable of quantifying a patient's risk using diagnostic biomarkers. The Medical Informatics Platform (MIP) is a distributed e-infrastructure federating large amounts of data coupled with machine-learning (ML) algorithms and statistical models to define the biological signature of the disease. The present study assessed (i) the accuracy of two ML algorithms, i.e., supervised Gradient Boosting (GB) and semi-unsupervised 3C strategy (Categorize, Cluster, Classify-CCC) implemented in the MIP and (ii) their contribution over the standard diagnostic workup. Methods: We examined individuals coming from the MIP installed across 3 Italian memory clinics, including subjects with Normal Cognition (CN, n = 432), Mild Cognitive Impairment (MCI, n = 456), and AD ( n = 451). The GB classifier was applied to best discriminate the three diagnostic classes in 1,339 subjects, and the CCC strategy was used to refine the classical disease categories. Four dementia experts provided their diagnostic confidence (DC) of MCI conversion on an independent cohort of 38 patients. DC was based on clinical, neuropsychological, CSF, and structural MRI information and again with addition of the outcome from the MIP tools. Results: The GB algorithm provided a classification accuracy of 85% in a nested 10-fold cross-validation for CN vs. MCI vs. AD discrimination. Accuracy increased to 95% in the holdout validation, with the omission of each Italian clinical cohort out in turn. CCC identified five homogeneous clusters of subjects and 36 biomarkers that represented the disease fingerprint. In the DC assessment, CCC defined six clusters in the MCI population used to train the algorithm and 29 biomarkers to improve patients staging. GB and CCC showed a significant impact, evaluated as +5.99% of increment on physicians' DC. The influence of MIP on DC was rated from "slight" to "significant" in 80% of the cases. Discussion: GB provided fair results in classification of CN, MCI, and AD. CCC identified homogeneous and promising classes of subjects via its semi-unsupervised approach. We measured the effect of the MIP on the physician's DC. Our results pave the way for the establishment of a new paradigm for ML discrimination of patients who will or will not convert to AD, a clinical priority for neurology., (Copyright © 2020 Redolfi, De Francesco, Palesi, Galluzzi, Muscio, Castellazzi, Tiraboschi, Savini, Nigri, Bottini, Bruzzone, Ramusino, Ferraro, Gandini Wheeler-Kingshott, Tagliavini, Frisoni, Ryvlin, Demonet, Kherif, Cappa and D'Angelo.)

Published
2020
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26. Keeping People with Dementia or Mild Cognitive Impairment in Employment: A Literature Review on Its Determinants.

Author

Silvaggi F, Leonardi M, Tiraboschi P, Muscio C, Toppo C, and Raggi A

Subjects
Executive Function, Humans, Workplace, Cognitive Dysfunction, Dementia, Employment
Abstract

Background: Approximately 10-20% of people with early onset dementias (EOD) or mild cognitive impairment (MCI) are aged under 65 and, due to extended working life and increasing prevalence of dementias, they more and more frequently will be present in the active workforce. This review aimed to synthesize the available information about the ability of people with EOD or MCI to retain their participation in the labor workforce. Methods : We searched SCOPUS and EMBASE for peer-reviewed papers that reported studies assessing work ability in employees with EOD or MCI that were published in the period of January 2010 to August 2019. Results : We selected four publications, in which 1012 participants with EOD or MCI were enrolled (41.2% males). Cognitive difficulties rather than motor dysfunction were found to reduce patients' ability to work. Two main themes emerged: management of dementia in the workplace and the impact of symptoms on working status. Conclusions : EOD and MCI impact on workforce participation by determining problems in executive functions. Although this review was based on a small sample of studies, it can be shown that support in the workplace may act as a facilitator to enhance workforce participation, and occupational health professionals can help patients with EOD or MCI continue working as much as possible.

Published
2020
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27. Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification.

Author

Presotto L, Iaccarino L, Sala A, Vanoli EG, Muscio C, Nigri A, Bruzzone MG, Tagliavini F, Gianolli L, Perani D, and Bettinardi V

Subjects
Aged, Aged, 80 and over, Alzheimer Disease diagnostic imaging, Databases, Factual, Female, Humans, Magnetic Resonance Imaging methods, Magnetic Resonance Imaging standards, Male, Middle Aged, Positron Emission Tomography Computed Tomography methods, Positron Emission Tomography Computed Tomography standards, Positron-Emission Tomography methods, Reproducibility of Results, Tomography, X-Ray Computed methods, Brain diagnostic imaging, Plaque, Amyloid diagnostic imaging, Positron-Emission Tomography standards, Prodromal Symptoms, Radiation Dosage, Tomography, X-Ray Computed standards
Abstract

The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification. PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N  = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT ( 18 F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global 18 F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVr CT, SUVr MRI ) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations. We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVr CT and SUVr MRI global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm). The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis.

Published
2018
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28. Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage.

Author

Vos SJ, Verhey F, Frölich L, Kornhuber J, Wiltfang J, Maier W, Peters O, Rüther E, Nobili F, Morbelli S, Frisoni GB, Drzezga A, Didic M, van Berckel BN, Simmons A, Soininen H, Kłoszewska I, Mecocci P, Tsolaki M, Vellas B, Lovestone S, Muscio C, Herukka SK, Salmon E, Bastin C, Wallin A, Nordlund A, de Mendonça A, Silva D, Santana I, Lemos R, Engelborghs S, Van der Mussele S, Freund-Levi Y, Wallin ÅK, Hampel H, van der Flier W, Scheltens P, and Visser PJ

Subjects
Adult, Aged, Aged, 80 and over, Alzheimer Disease complications, Biomarkers metabolism, Cognitive Dysfunction etiology, Disease Progression, Female, Humans, Male, Middle Aged, Neuropsychological Tests, Prevalence, Prognosis, Survival Analysis, Alzheimer Disease epidemiology, Cognitive Dysfunction epidemiology
Abstract

Three sets of research criteria are available for diagnosis of Alzheimer's disease in subjects with mild cognitive impairment: the International Working Group-1, International Working Group-2, and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage according to these criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and available biomarkers to classify subjects as prodromal Alzheimer's disease according to International Working Group-1 and International Working Group-2 criteria and in the high Alzheimer's disease likelihood group, conflicting biomarker groups (isolated amyloid pathology or suspected non-Alzheimer pathophysiology), and low Alzheimer's disease likelihood group according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures were the proportion of subjects with Alzheimer's disease at the mild cognitive impairment stage and progression to Alzheimer's disease-type dementia. We performed survival analyses using Cox proportional hazards models. According to the International Working Group-1 criteria, 850 (53%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 50% compared to 21% for subjects without prodromal Alzheimer's disease. According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 61% compared to 22% for subjects without prodromal Alzheimer's disease. According to the National Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high Alzheimer's disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220 (29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low Alzheimer's disease likelihood group. The 3-year progression rate to Alzheimer's disease-type dementia was 59% in the high Alzheimer's disease likelihood group, 22% in the isolated amyloid pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low Alzheimer's disease likelihood group. Our findings support the use of the proposed research criteria to identify Alzheimer's disease at the mild cognitive impairment stage. In clinical settings, the use of both amyloid and neuronal injury markers as proposed by the National Institute of Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials, selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer's disease likelihood group or the International Working Group-2 prodromal Alzheimer's disease group could be considered., (© The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Published
2015
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